Use of prototype quantum computer opened up to outsiders

A prototype quantum computer being developed in Japan will be made freely available from Nov. 27 to allow more engineers the chance to improve it.

The National Institute of Informatics and other research agencies hope to commercialize a domestic quantum computer by the end of fiscal 2019 in the face of intensifying global competition.

“We will seek to further improve the prototype so that the quantum computer can eventually tackle the various problems that are out there in society,” said Yoshihisa Yamamoto, the program manager for the research group.



Quantum Programming Language

Microsoft has announced at its Ignite conference a new programming language designed to work both on present quantum simulators and upcoming quantum computers the company is building.

The quantum programming language is designed to work with Microsoft’s Visual Studio integrated development environment (IDE), which is already familiar among developers of programs for the Windows operating system, websites, and mobile apps. Developers can perform common tasks, such as debugging and auto-complete, but will also have the ability to call quantum subroutines, and to write sequences of programming instructions for a complete quantum program, announced Microsoft.


Banking Applications in Quantum Computing

See the full article from The Australian.

Australia’s Commonwealth Bank announced that it has developed a quantum computer simulator. This will help develop applications across a variety of industries rather than wait for the hardware to become available.

Applications for a large, complex bank like CBA start with so-called Monte Carlo simulations, where the impact of risk is assessed on the full range of scenarios under consideration. Under classical computing, it takes about a day to work out the risk position of the bank.

Quantum computing would deliver the same outcome in a matter of minutes, enabling more dynamic decision-making as a result of real-time data feeds.

Trading positions could be known in real time, with investment strategies chosen after consideration of millions of different scenarios. Beyond such base-level applications, the potential is mostly unknown because problem-solving in business is constrained by the limits of classical computing.